Input sensing using overlapping code division multiplexing (cdm)

ABSTRACT

Sensing systems and methods that utilize zero row sum code division multiplexing (CDM) drive matrices to reduce or eliminate radiative emissions. Measurements corresponding to an input received at a sensing region of the input device are obtained by driving a first subset of transmitters of the input device according to a first portion of a CDM drive matrix, wherein the CDM matrix is a zero row sum matrix, and obtaining first measurement signals with the plurality of receivers, and driving a second subset of the transmitters according to a second portion of the CDM drive matrix, wherein the first and second subsets of transmitters include at least one transmitter in common, and obtaining second measurement signals with the plurality of receivers. An image of the input may be generated based on the obtained measurements.

TECHNICAL FIELD

The present disclosure generally provides systems and methods for inputsensing using code division multiplexing (CDM).

BACKGROUND

Input devices, including touch sensor devices (also commonly calledtouchpads or proximity sensor devices), as well as fingerprint sensordevices, are widely used in a variety of electronic systems. Touchsensor devices typically include a sensing region, often demarked by asurface, in which the touch sensor device determines the presence,location, force, and/or motion of one or more input objects. Touchsensor devices may be used to allow a user to provide user input tointeract with the electronic system. Fingerprint sensor devices alsotypically include a sensing region in which the fingerprint sensordevice determines presence, location, motion, and/or features of afingerprint or partial fingerprint. Finger print sensor devices may beused for purposes relating to user authentication or identification of auser.

Touch sensor devices and fingerprint sensor devices may thus be used toprovide interfaces for the electronic system. For example, touch sensordevices and fingerprint sensor devices are often used as input devicesfor larger computing systems such as opaque touchpads and fingerprintreaders integrated in or peripheral to notebook or desktop computers.Touch sensor devices and fingerprint sensors are also often used insmaller computing systems such as touch screens integrated in mobiledevices such as smartphones and tablets.

SUMMARY

According to an embodiment, a method of input sensing using an inputdevice is provided. The method may include receiving, at a sensingregion of the input device, an input, and obtaining, using a pluralityof receivers of the input device, measurements corresponding to theinput, wherein obtaining the measurements includes driving a firstsubset of transmitters of the input device according to a first portionof a CDM transmitter control, or drive, matrix, wherein the CDM matrixis a zero row sum matrix, and obtaining first measurements with theplurality of receivers, and driving a second subset of the transmittersaccording to a second portion of the CDM drive matrix, wherein the firstand second subsets of transmitters include at least one transmitter incommon, and obtaining second measurements with the plurality ofreceivers. The method may also include generating, by a processingsystem of the input device, an image of the input based on the obtainedfirst and second measurements. The obtaining measurements may furtherinclude driving a third subset of the transmitters according to the CDMdrive matrix, wherein the third subset of transmitters includes at leastone transmitter in common with the first subset of transmitters or thesecond subset of transmitters, and obtaining third measurements with theplurality of receivers. The generating an image may include processingthe first measurements, the second measurements and the thirdmeasurements.

According to another embodiment, an input device for sensing a biometricobject is provided. The input device may include a surface correspondingto a sensing region, wherein the sensing region is configured to receiveone or more inputs, e.g., one or more objects such as one or morefingers, transmitters configured to be driven with transmitter signals,and receivers configured to obtain measurement signals by driving afirst subset of the transmitters according to a first portion of a CDMdrive matrix, wherein the CDM matrix is a zero row sum matrix, andobtaining first measurement signals with the receivers, and thereafterdriving a second subset of the transmitters according to a secondportion of the CDM drive matrix, wherein the first and second subsets oftransmitters include at least one transmitter in common, and obtainingsecond measurement signals with the receivers. The input device may alsoinclude a processing system, configured to generate an image of the oneor more inputs based on the obtained measurement signals.

According to yet another embodiment, a non-transitory computer-readablemedium having processor-executable instructions stored thereon isprovided. The processor-executable instructions include instructions forperforming input sensing using an input device. The processor-executableinstructions, when executed by a processing system, enable theprocessing system to implement a method which includes obtaining, viareceivers of the input device, measurement signals corresponding to oneor more inputs received at a sensing region of the input device bydriving a first subset of transmitters of the input device according toa first portion of a CDM drive matrix, wherein the CDM matrix is a zerorow sum matrix, and obtaining first measurement signals with thereceivers, and driving a second subset of the transmitters according toa second portion of the CDM drive matrix, wherein the first and secondsubsets of transmitters include at least one transmitter in common, andobtaining second measurement signals with the receivers. Theprocessor-executable instructions also enable the processing system togenerate an image of the one or more inputs by processing the firstmeasurement signals and the second measurement signals.

In certain aspects, all driving and measurement iterations for a firstsubset of transmitters are performed before any driving and measurementiterations for a second subset of transmitters are performed.

According to a further embodiment, a method of operating an input devicehaving a plurality of receivers and a plurality of transmitters isprovided. The method may include receiving, at a sensing region of theinput device, one or more inputs, driving the plurality of transmitters,and obtaining measurement signals using the plurality of transmitterswhile the transmitters are being driven. The obtaining measurementsignals may include obtaining, using a first subset of the plurality ofreceivers of the input device, first measurement signals correspondingto the input, and thereafter obtaining, using a second subset of theplurality of receivers of the input device, second measurement signalscorresponding to the input, wherein the second subset includes at leastone receiver in common with the first subset. The method may furtherinclude determining a difference between the first measurement signalsand the second measurement signals corresponding to the at least onereceiver in common, and adjusting one of the first measurement signalsor the second measurement signals based on the determined difference,e.g., to thereby remove a difference in noise detected between the firstand second measurement signals.

Reference to the remaining portions of the specification, including thedrawings and claims, will realize other features and advantages of thepresent invention. Further features and advantages of the presentinvention, as well as the structure and operation of various embodimentsof the present invention, are described in detail below with respect tothe accompanying drawings. In the drawings, like reference numbersindicate identical or functionally similar elements.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING(S)

The detailed description is described with reference to the accompanyingfigures. The use of the same reference numbers in different instances inthe description and the figures may indicate similar or identical items.

FIG. 1 is a block diagram depicting an example input device, accordingto one or more embodiments.

FIGS. 2A-2B are block diagrams depicting further example input devices,according to some embodiments.

FIG. 3 depicts an orthogonal grid of transmitter electrodes and receiverelectrodes of an input device according to one or more embodiments.

FIG. 4A illustrates an example of zero row sum CDM for radiated emissionmitigation, according to one or more embodiments.

FIG. 4B illustrates an example of interleaved zero row sum CDM forradiated emission mitigation, according to one or more embodiments.

FIG. 5 illustrates examples of odd dimension matrices, according to oneor more embodiments.

FIG. 6A shows an example of an of odd dimension CDM7 matrix, accordingto one or more embodiments.

FIG. 6B shows an example of a CDM matrix including 3 overlapping CDM7matrices of FIG. 6A, according to one or more embodiments.

FIG. 6C shows an example of a circulant matrix of dimension 7, accordingto one or more embodiments.

FIG. 6D shows an example of an even dimension CDM 8 matrix, according toone or more embodiments.

FIG. 7 shows a full inverse (21×21) matrix for the matrix of FIG. 6B,according to one or more embodiments.

FIG. 8 shows an example of deconvolved image data for two fingerstouching the input device screen with a zero row sum CDM7 in thepresence of display noise, according to an embodiment.

FIG. 9 shows an example of the deconvolved image data (FIG. 8) for twofingers touching the input device screen with a zero row sum CDM7 in thepresence of display noise after undergoing a stitching and recombinationprocess, according to an embodiment.

FIG. 10 shows an example of the deconvolved image data (FIG. 9) for twofingers touching the input device screen with a zero row sum CDM7 in thepresence of display noise after undergoing a stitching and recombinationprocess and after removing common mode noise and artifacts, according toan embodiment.

FIG. 11 shows data acquired in two receiver firing steps with anoverlapping electrode, and results of a stitching procedure to correctfor a noise difference between the steps, according to an embodiment.

FIG. 12 shows data acquired in two receiver firing steps with twooverlapping electrodes, and results of a stitching procedure to correctfor a noise difference between the firing steps, according to anembodiment.

FIG. 13 is a flowchart depicting a process using lower-order zero rowsum CDM according to an embodiment.

DETAILED DESCRIPTION

The following detailed description is exemplary in nature and is notintended to limit the disclosure or the application and uses of thedisclosure. Furthermore, there is no intention to be bound by anyexpressed or implied theory presented in the preceding background,summary and brief description of the drawings, or the following detaileddescription.

In one or more embodiments, input devices, including touch sensordevices and fingerprint sensor devices, utilize code divisionmultiplexing (CDM) with respect to transmitter signals driven ontotransmitter electrodes, in order to enhance the signal level. In someembodiments, the CDM order, corresponding to the amount of transmittersbeing simultaneously driven, is equivalent to the total number oftransmitter electrodes such that all transmitter electrodes aresimultaneously driven for a plurality of imaging or sensing iterations.In some embodiments, lower-order CDM may be used wherein a fewer numberof transmitter electrodes are simultaneously driven. For example,separate portions or blocks of a larger CDM drive matrix may be used todrive separate or overlapping portions of the transmitter electrodes atdifferent times. Lower-order CDM provide for various advantagesincluding reduction in peak power, reduction in average power, reductionin sensor self-heating, and reduction in computational complexity. Theseadvantages may be achieved in a flexibly configurable manner to meet thedesired power specifications for various implementations of touch sensordevices and fingerprint sensor devices.

FIG. 1 is a block diagram depicting an example input device 100according to one or more embodiments. The input device 100 may beconfigured to provide input to an electronic system (not shown forsimplicity). As used in this document, the term “electronic system” or“electronic device” broadly refers to any system capable ofelectronically processing information. Some non-limiting examples ofelectronic systems include personal computers of all sizes and shapes,such as desktop computers, laptop computers, netbook computers, tablets,web browsers, e-book readers, personal digital assistants (PDAs), andwearable computers such as smart watches and activity tracker devices).Additional examples of electronic systems include composite inputdevices, such as physical keyboards that include input device 100 andseparate joysticks or key switches. Further examples of electronicsystems include peripherals such as data input devices (including remotecontrols and mice), and data output devices (including display screensand printers). Other examples include remote terminals, kiosks, andvideo game machines (e.g., video game consoles, portable gaming devices,and the like). Other examples include communication devices (includingcellular phones, such as smart phones), and media devices (includingrecorders, editors, and players such as televisions, set-top boxes,music players, digital photo frames, and digital cameras). Additionally,the electronic system or device may be a host or a slave to the inputdevice.

The input device 100 can be implemented as a physical part of theelectronic system, or can be physically separate from the electronicsystem. As appropriate, the input device 100 may communicate with partsof the electronic system using any one or more of the following: buses,networks, and other wired or wireless interconnections. Examples includeInter-Integrated Circuit (I²C), Serial Peripheral Interface (SPI),Personal System/2 (PS/2), Universal Serial Bus (USB), Bluetooth®, radiofrequency (RF), and Infrared Data Association (IrDA).

In one or more embodiments, the input device 100 comprises one or moresensing elements for detecting user input. The input device 100 mayinclude a sensor 105, which comprises one or more sensing elementsconfigured to sense input provided by one or more input objects in asensing region. Examples of input objects include fingers, styli, andhands. The sensing region may encompass any space above, around, inand/or near the sensor 105 in which the input device 100 is able todetect user input (e.g., user input provided by one or more inputobjects). The size, shape, and/or location of the sensing region mayvary from embodiment to embodiment and depending on actualimplementations. In some embodiments, the sensing region extends from asurface of the input device 100 in one or more directions into spaceuntil signal-to-noise ratios prevent sufficiently accurate objectdetection. The distance to which this sensing region extends in aparticular direction, in various embodiments, may be on the order ofless than a millimeter, millimeters, centimeters, or more, and may varywith the type of sensing technology used and/or the accuracy desired.Thus, some embodiments sense input that comprises no physical contactwith any surfaces of the input device 100, contact with an input surface(e.g., a touch surface and/or screen) of the input device 100, contactwith an input surface of the input device 100 coupled with some amountof applied force or pressure, or a combination thereof. In variousembodiments, input surfaces may be provided by surfaces of sensorsubstrates within which or on which sensor elements are positioned, orby face sheets or other cover layers positioned over sensor elements. Invarious embodiments, input surfaces may be provided by one or moresurfaces of a casing or a housing of the input device 100.

The input device 100 may utilize various sensing technologies to detectuser input in the sensing region. Example sensing technologiescapacitive, elastive, resistive, inductive, magnetic, acoustic,ultrasonic, and/or optical techniques. In some embodiments, the inputdevice 100 may utilize capacitive sensing technologies to detect userinputs. For example, a sensing region may include one or more capacitivesensing elements (e.g., sensor electrodes) to create an electric fieldby the applied voltage and/or current. The input device 100 may detectinputs based on changes in capacitance of the sensing elements. Forexample, an object in contact with (or close proximity to) the electricfield may cause changes in the voltage and/or current in the sensingelements. Such changes may be detected as “signals” indicative of userinput. The sensing elements may be arranged in arrays, or other regularor irregular patterns, or other configurations to detect inputs atmultiple points within the sensing region. In some implementations,separate sensing elements may be ohmically shorted together to formlarger sensor electrodes. Some other implementations may utilizeresistive sheets, which may be uniformly resistive.

Some capacitive sensing technologies may be based on “self-capacitance”(also referred to as “absolute capacitance”) and/or “mutual capacitance”(also referred to as “transcapacitance”). Absolute capacitance sensingmethods detect changes in the capacitive coupling between one or moresensing elements and a substantially grounded touching object or objectin proximity. For example, an input object near one or more sensingelements may alter the electric field near the sensing elements, thuschanging the measured capacitive coupling between two or more sensorelectrodes of the sensing elements. In some embodiments, the inputdevice 100 may implement absolute capacitance sensing by modulatingsensor electrodes with respect to a reference voltage and detecting thecapacitive coupling between the sensor electrodes and input objects. Thereference voltage may be substantially constant or may vary. In someaspects, the reference voltage may correspond to a ground potential.

Transcapacitance (or transcapacitive or trans-capacitive) sensingmethods detect changes in the capacitive coupling between sensorelectrodes. In various embodiments, an input object near the sensorelectrodes alters the electric field between the sensor electrodes, thuschanging the measured capacitive coupling. In one implementation, atranscapacitive sensing method operates by detecting the capacitivecoupling between one or more transmitter sensor electrodes (also“transmitter electrodes” or “drive electrodes”) and one or more receiversensor electrodes (also “receiver electrodes” or “pickup electrodes”).Transmitter sensor electrodes may be modulated relative to a referencevoltage to transmit transmitter signals. Receiver sensor electrodes maybe held substantially constant relative to the reference voltage tofacilitate receipt of resulting signals. The reference voltage may be,for example, a substantially constant voltage or system ground. In someembodiments, transmitter sensor electrodes and receiver sensorelectrodes may both be modulated. The transmitter electrodes aremodulated relative to the receiver electrodes to transmit transmittersignals and to facilitate receipt of resulting signals. A resultingsignal may comprise effects corresponding to one or more transmittersignals, and/or to one or more sources of environmental interference(e.g. other electromagnetic signals). Sensor electrodes may be dedicatedtransmitters or receivers, or may be configured to both transmit andreceive.

Some implementations of the input device 100 are configured to provideimages that span one, two, three, or higher dimensional spaces. Theinput device 100 may have a sensor resolution that varies fromembodiment to embodiment depending on factors such as the particularsensing technology involved and/or the scale of information of interest.In some embodiments, the sensor resolution is determined by the physicalarrangement of an array of sensing elements, where smaller sensingelements and/or a smaller pitch can be used to define a higher sensorresolution.

The input device 100 may be implemented as a fingerprint sensor having asensor resolution high enough to capture discriminative features of afingerprint. In some implementations, the fingerprint sensor has aresolution sufficient to capture minutia (including, e.g., ridge endingsand bifurcations), orientation fields (sometimes referred to as “ridgeflows”), and/or ridge skeletons. These are sometimes referred to aslevel 1 and level 2 features, and in an embodiment, a resolution of atleast 250 pixels per inch (ppi) is capable of reliably capturing thesefeatures. In some implementations, the fingerprint sensor has aresolution sufficient to capture higher level features, such as sweatpores or edge contours (i.e., shapes of the edges of individual ridges).These are sometimes referred to as level 3 features, and in anembodiment, a resolution of at least 750 pixels per inch (ppi) iscapable of reliably capturing these higher level features.

In some embodiments, a fingerprint sensor is implemented as a placementsensor (also “area” sensor or “static” sensor) or a swipe sensor (also“slide” sensor or “sweep” sensor). In a placement sensor implementation,the sensor is configured to capture a fingerprint input as the user'sfinger is held stationary over the sensing region. The placement sensormay include a two dimensional array of sensing elements capable ofcapturing a desired area of the fingerprint in a single frame. In aswipe sensor implementation, the sensor is configured to capture to afingerprint input based on relative movement between the user's fingerand the sensing region. The swipe sensor may include a linear array or athin two-dimensional array of sensing elements configured to capturemultiple frames as the user's finger is swiped over the sensing region.The multiple frames may then be reconstructed to form an image of thefingerprint corresponding to the fingerprint input. In someimplementations, the sensor is configured to capture both placement andswipe inputs.

In some embodiments, a fingerprint sensor is configured to capture lessthan a full area of a user's fingerprint in a single user input(referred to herein as a “partial” fingerprint sensor). Typically, theresulting partial area of the fingerprint captured by the partialfingerprint sensor is sufficient for the system to perform fingerprintmatching from a single user input of the fingerprint (e.g., a singlefinger placement or a single finger swipe). Some example imaging areasfor partial placement sensors include an imaging area of 100 mm² orless. In another example embodiment, a partial placement sensor has animaging area in the range of 20-50 mm². In some implementations, thepartial fingerprint sensor has an input surface that is the same sizethe imaging area.

Referring back to FIG. 1 according to one or more embodiments, the inputdevice 100 includes a processing system 110 as shown. The processingsystem 110 comprises parts of or all of one or more integrated circuits(ICs) and/or other circuitry components. The processing system 110 iscoupled to the sensor 105, and is configured to detect input in thesensing region using sensing hardware of the sensor 105.

The processing system 110 may include driver circuitry configured todrive sensing signals with sensing hardware of the input device 100and/or receiver circuitry configured to receive resulting signals withthe sensing hardware. For example, a processing system may be configuredto drive transmitter signals onto transmitter electrodes of the sensor105, and/or receive resulting signals detected via receiver electrodesof the sensor 105.

The processing system 110 may include a non-transitory computer-readablemedium having processor-executable instructions (such as firmware code,software code, and/or the like) stored thereon. The processing system110 can be implemented as a physical part of the sensor 105, or can bephysically separate from the sensor 105. Also, constituent components ofthe processing system 110 may be located together, or may be locatedphysically separate from each other. For example, the input device 100may be a peripheral coupled to a computing device, and the processingsystem 110 may comprise software configured to run on a centralprocessing unit of the computing device and one or more ICs (e.g., withassociated firmware) separate from the central processing unit. Asanother example, the input device 100 may be physically integrated in amobile device, and the processing system 110 may comprise circuits andfirmware that are part of a main processor of the mobile device. Theprocessing system 110 may be dedicated to implementing the input device100, or may perform other functions, such as operating display screens,driving haptic actuators, etc.

The processing system 110 may operate the sensing element(s) of thesensor 105 of the input device 100 to produce electrical signalsindicative of input (or lack of input) in a sensing region. Theprocessing system 110 may perform any appropriate amount of processingon the electrical signals in producing the information provided to theelectronic system. For example, the processing system 110 may digitizeanalog electrical signals obtained from sensor electrodes. As anotherexample, the processing system 110 may perform filtering or other signalconditioning. As yet another example, the processing system 110 maysubtract or otherwise account for a baseline, such that the informationreflects a difference between the electrical signals and the baseline.As yet further examples, the processing system 110 may determinepositional information, recognize inputs as commands, recognizehandwriting, match biometric samples, and the like.

The sensing region of the input device 100 may overlap part or all of anactive area of a display device, for example, if the sensor 105 providesa touch screen interface. The display device may be any suitable type ofdynamic display capable of displaying a visual interface to a user,including an inorganic light-emitting diode (LED) display, organic LED(OLED) display, cathode ray tube (CRT), liquid crystal display (LCD),plasma display, electroluminescence (EL) display, or other displaytechnology. The display may be flexible or rigid, and may be flat,curved, or have other geometries. The display may include a glass orplastic substrate for thin-film transistor (TFT) circuitry, which may beused to address display pixels for providing visual information and/orproviding other functionality. The display device may include a coverlens (sometimes referred to as a “cover glass”) disposed above displaycircuitry and above inner layers of the display module, and the coverlens may also provide an input surface for the input device 100.Examples of cover lens materials include optically clear amorphous solidmaterials, such as chemically hardened glass, and optically clearcrystalline structures, such as sapphire. The input device 100 and thedisplay device may share physical elements. For example, some of thesame electrical components may be utilized for both displaying visualinformation and for input sensing with the input device 100, such asusing one or more display electrodes for both display updating and inputsensing. As another example, the display screen may be operated in partor in total by the processing system 110 in communication with the inputdevice.

FIGS. 2A-2B are block diagrams depicting further input devices accordingto some embodiments. In FIG. 2A, the input device 100 is shown asincluding a touch sensor 205 a. The touch sensor 205 a is configured todetect position information of an input object within the sensing region220 a, according to an embodiment. The input object may include a finger240 b or a stylus 240 a, as shown in FIG. 2A. The sensing region 220 amay include an input surface having a larger area than the input object.The touch sensor 205 a may include an array of sensing elements with aresolution configured to detect a location of a touch to the inputsurface. The input device 100 may also be configured to detect presence,force, and/or motion of an input object with the touch sensor 205 a. Theinput object may include more than one object.

In FIG. 2B, the input device 100 is shown as including a fingerprintsensor 205 b. The fingerprint sensor 205 b is configured to capture afingerprint from a finger 240 b. In one embodiment, the fingerprintsensor 205 b is disposed underneath a cover layer 212 that provides aninput surface for the fingerprint to be placed on or swiped over thefingerprint sensor 205 b. The sensing region 220 b may include an inputsurface with an area larger than, smaller than, or similar in size to afull fingerprint. The fingerprint sensor 205 b may have an array ofsensing elements with a resolution configured to detect surfacevariations of the finger 240 b, and the fingerprint sensor 205 b has ahigher resolution than the touch sensor 205 a of FIG. 2A.

FIG. 3 depicts an orthogonal 17×17 grid of transmitter electrodes,T1-T17, and receiver electrodes, R1-R17, of an example input deviceaccording to one or more embodiments. In FIG. 3, the input device isbeing driven by a 17×17 drive matrix. It will be appreciated that a17×17 grid is shown for illustrative purposes, but that variousimplementations of an input device may be of any size, having even orodd numbers of electrodes—including, for example, 15×15, 15×27, 17×17,17×27, 31×31, 16×16, 22×22, 56×96, 80×80, 88×116, 56×144, 72×80, andother electrode grid sizes. It will further be appreciated that althougha grid with transmitter electrodes and receiver electrodes orthogonal toone another in a bars and stripes configuration is used herein as anexample, other example implementations of a capacitive input device mayutilize other configurations of transmitter electrodes and receiverelectrodes—including, for example, single-layer configurations withinterdigitated electrodes, matrix configurations where each pixelcorresponds to an electrode plate, orthogonal diamond configurations,etc. It will be appreciated that although the illustrative examplediscussed in this embodiment is provided in the context of a capacitiveinput device, the principles described in this embodiment and others mayalso be applied to other types of input devices, such as acoustic orultrasonic input devices, or other device that also utilizestransmitters and receivers.

As shown in FIG. 3, the transmitter electrodes T1-T17 may be drivenaccording to various CDM driving techniques or schemes. For example, inone CDM driving scheme, where the CDM order is 17 (CDM17), alltransmitter electrodes T1-T17 are simultaneously driven with differentcodings, with each row of the CDM drive matrix each having a same rowsum, over 17 imaging iterations (corresponding to a 17×17 drive matrix).Thus, with all of transmitter electrodes T1-T17 being driven 17 times,this would result in relatively high peak power, average power, sensorself-heating, and computational complexity. The information capturedthrough the CDM technique is then deconvolved or decoded using theinverse (for a non-zero row sum drive matrix) or transpose (for a zerorow sum drive matrix) of the drive matrix to obtain an imagecorresponding to an input.

Certain sensor applications, such as in automotive subsystems, may havea very stringent set of electromagnetic radiation emission requirementsthey may not exceed; one such standard is CISPR25 [Comité InternationalSpécial des Perturbations Radioélectriques, English: InternationalSpecial Committee on Radio Interference]. The CISPR25 standard includesemission limits versus frequency and has three measurement limits versusfrequency as measured on a spectrum analyzer: peak, quasi-peak andaverage. In some embodiments, a capacitive touch sensing system used ina vehicle may inherently radiate because the touch sensing systemdetects a finger by changing voltages on the sensor electrodes andmeasuring changes in capacitance on those electrodes. Every electrodemay become an antenna and may emit radiation. When CDM schemes areintroduced to increase the signal-to-noise ratio, the radiated emissionsmay further increase according to the row sum of the transmittercontrol/driving CDM matrix.

In an embodiment, zero row sum drive matrices are used to drive sensorelectrodes to allow deconvolution of the raw measurements to recover theoriginal signals on each electrode to within an arbitrary constant,which can be conveniently set to provide a zero amplitude baseline in a2D image. Zero row sum matrices have the desirable property that the sumof the emissions from the active (driven) set of transmitter electrodes(“transmitters”) in the CDM drive pattern sum to zero, which means theemitted radiation from half of the active transmitters radiate or couple180° out of phase with the other half of the active transmitters and thenet radiated emission is zero or negligible as shown in FIG. 4A and FIG.4B. FIG. 4A shows an example of zero row sum CDM radiated emissions. Inparticular, a single drive iteration is shown using a zero row sum CDM7matrix to drive a contiguous subset of 7 transmitter electrodes (top 7transmitter electrodes in FIG. 4A). Note that the middle (4^(th))electrode of the 7 driven electrodes is not transmitting (0) for theparticular drive iteration shown. FIG. 4B shows an example ofinterleaved zero row sum CDM using a CDM7 matrix to drive non-contiguoustransmitter electrodes as will be discussed in more detail below. In thespecific interleaved drive iteration shown in FIG. 4B, every othertransmitter electrode is driven using CDM7, wherein the non-driventransmitter electrode (9^(th) from top in example shown) may be drivenin a subsequent CDM drive iteration.

A certain class of matrices have the elegant property, namely

{right arrow over (M)} ^(T) {right arrow over (M)}=d{right arrow over(I)}−{right arrow over (Ones)}.

That is, driving a 2-dimensional (2D) transcapacitive image sensor witha suitable matrix, M, then deconvolving the acquired data with thetranspose of that matrix yields the dimension of the matrix times thetransmitter's row data minus the average of all the rows' data in theCDM set. This recognition increases flexibility for driving sensorshaving odd numbers of transmitters.

Lowering radiated emissions may be useful for simultaneously performingtouch sensing and meeting automotive radiated emissionspecifications/standards. When using square wave waveforms, there may bean infinite number of harmonics and many may fall within frequency bandswhere radiated emission limits exist. Using Zero Row Sum drivingmatrices reduce those harmonics as well. Even using sine wave sensing,reducing the emissions at that single frequency may still be neededdepending on particular requirements and possible future modificationsto the international specifications.

In certain embodiments, CDM drive matrices M have the three properties:

-   -   1. The matrix elements are from the set {−1, 0, +1};    -   2. The sum of each row is zero, i.e., Σ_(j)M_(ij)=0; and    -   3. The transpose of M times M has the relationship:

$\begin{matrix}{\frac{M^{T} \cdot M}{d} = {{I - \frac{\begin{bmatrix}1 & \ldots & 1 \\\vdots & \ddots & \vdots \\1 & \ldots & 1\end{bmatrix}}{d}}=={I - {{I \cdot \frac{1}{d}}{\sum_{i}{pixels}_{i}}}}=={I - {I \cdot {\langle{pixels}_{i}\rangle}}}}} & ( {{Eq}.\mspace{11mu} 1} )\end{matrix}$

-   -   -   where d is the dimension of the CDM matrix M and (pixel_(i))            is the average of the pixels within a CDM group or block.

Examples of CDM drive matrices of dimension 3, 5 and 7 are shown in FIG.5. These odd zero row sum matrices furthermore possess the property thatthe transpose of M is plus or minus the matrix M according to thedimension d, i.e., if (d−1)/2 is even then M^(T)=M, if (d−1)/2 is oddM^(T)=−M.

If the right hand side of Eq. 1 is averaged over the pixels (the iindex) it is identically 0. That property implies that each CDM block'sresulting values average (and sum) to zero, so if multiple CDM blocksare required for a larger sensor, the complete deconvolved profile of anobject touching the sensor may have discontinuities. Also, afterdeconvolution, each column of the CDM block has zero mean, so there is 1free parameter per CDM block, per receiver, to be determined toreconstruct the original image. As an example, for 3 CDM blocks and 27physical receivers there will be 3×27=81 free parameters to bedetermined. Additionally, in situations where the transmitters of smallCDM blocks are covered with two or more objects (e.g., fingers), it maybe difficult to determine the original signal and to reconstruct orrecover the original image in various situations. Therefore, it isdesirable to reduce the number of free parameters to be determined.

According to certain embodiments, multiple overlapping CDM blocks areused, wherein multiple overlapping CDM blocks are “stitched” together toform a larger CDM drive matrix. Such embodiments advantageously reducethe number of free parameters to be determined, improves efficiency ofthe reconstruction of the original images detected, and preserves thebenefits of Zero Row Sum CDM while reducing or eliminating negativeside-effects of artifacts such as baseline errors and Low Ground Mass(LGM) effects, improving large object discrimination, display noiseremoval, etc. LGM effects may show up as a deformation of large objectsignals or the presence of spurious negative signals at the intersectionbetween touched receivers and transmitters, as examples.

For example, in an embodiment, each constituent CDM block making up thelarger CDM block overlaps with at least one other constituent CDM block;that is, each constituent CDM block drives at least one transmitter incommon with another constituent CDM block. In an embodiment, any numberof constituent CDM blocks may be used, wherein each constituent CDMblock has at least one (driven) transmitter in common with one of theother constituent CDM blocks.

According to an embodiment, a method of input sensing using an inputdevice driven with such a zero row sum CDM matrix may include receiving,at a sensing region of the input device, an input, and obtaining, usinga plurality of receivers of the input device, measurements correspondingto the input, wherein obtaining the measurement signals includes drivinga first subset of transmitters of the input device according to a firstportion of a CDM drive matrix and obtaining first measurement signalswith the plurality of receivers, and driving a second subset of thetransmitters according to a second portion of the CDM drive matrix,wherein the first and second subsets of transmitters include at leastone transmitter in common, and obtaining second measurement signals withthe plurality of receivers. In certain aspects, during each driving stepor iteration, the measurement signals obtained or acquired by theplurality of receivers are simultaneously obtained or acquired with thedriving of the corresponding subset of transmitters.

As an example, FIG. 6A shows an example of a Zero Row Sum CDM7 block600, and FIG. 6B shows an example of a 15×21 CDM transmitter controlmatrix (or drive matrix) 610 including three overlapping CDM7 blocks 600of FIG. 6A (identified in FIG. 6B as blocks 1, 2 and 3) on a touchsensor including 15 transmitter rows. Consecutive rows of the drivematrix represent consecutive drive iterations or periods in time, andthe columns indicate the polarity (+1 and −1) or not transmitting (0)for each transmitter. The touch sensor may include any number ofreceiver rows, for example 17 receiver rows (15×17) or 21 receiver rows(15×21) or 27 receiver rows (15×27), etc. As shown in FIG. 6B,constituent CDM blocks 1 and 2 overlap at transmitter electrodes 5, 6and 7, and constituent CDM blocks 2 and 3 overlap at transmitterelectrodes 9, 10 and 11. It should be appreciated that the blocks mayoverlap at different transmitters, or overlap with fewer or moretransmitters and can be applied to any permutation of columns or rows.

In certain embodiments, other types of matrices may be used, for examplecirculant matrices and even dimension matrices, with the same CDM drivematrix properties described above. For example, a zero row sum CDM drivematrix may include a circulant matrix, an odd dimension matrix or aneven dimension matrix. FIG. 6C shows an example of a circulant matrix ofdimension 7, according to one or more embodiments. FIG. 6D shows anexample of an even dimension CDM 8 matrix, according to one or moreembodiments.

Advantages of driving electrodes using CDM matrices include an increasein the Signal-to-Noise Ratio (SNR) by roughly the square root of the CDMorder, e.g., sqrt7 improvement for CDM7. The advantages of using zerorow sum CDM matrices also includes a reduction in radiated emissions,especially when used in the context of transcapacitive touch sensing.According to certain embodiments, a higher order CDM matrix may be usedso that it spans a larger distance and/or a smaller CDM matrix may bespread out to span a larger distance, e.g., driving non-contiguoustransmitters in an interleaved manner such as every other transmitterdriven for the span of the CDM matrix or every third transmitter drivenfor the span of the CDM matrix, etc.

Certain embodiments and advantages are now illustrated with figures.FIG. 8 shows an example of a deconvolved transcapacitive sensing imagedata acquired with the CDM drive matrix 610 of FIG. 6B (including threeoverlapping CDM7 matrices) with two fingers on a touch sensor having 15transmitter rows and 27 receiver columns), according to one or moreembodiments. In an embodiment with 27 receivers, the 3 deconvolved CDMblocks of the 2D image are obtained by applying:

Trans=(obj.cdmMatrixInvFull*transConvolved)/obj.cdmOrder;

which in this example embodiment is a matrix operation of the type:

(matrix 21×27)=(matrix 21×21)*(matrix 21×27)/cmdOrder, with cdmOrder=7.

FIG. 7 illustrates the full inverse matrix 700 (cdmMatrixInvFull) of theCDM drive matrix 610 shown in FIG. 6B, and the 21×27 transConvolvedmatrix corresponds to the measurements acquired by the 27 receiverelectrodes over the 21 transmitter driving iterations of the CDM drivematrix (i.e., each row of the CDM drive matrix 610 corresponds to adrive iteration where all (active) receiver electrodes may sense asignal simultaneously). The peaks reflect the shape and position of thefingers and subsequent Image Frame Processing (IFP) may be used toclassify and process the image to obtain image information as desired.In an embodiment, a stitching and recombination procedure may beperformed to obtain the full image. For example, stitching together andrecombining the CDM blocks may be performed to obtain a single column ofdata per physical receiver. In the particular example being used,stitching and recombination may be performed to obtain the 15×27 image(corresponding to 15 transmitter electrodes and 27 receiver electrodesin this example). In one particular embodiment, the stitching andrecombination may be accomplished (in Matlab® notation) for thisparticular example as follows:

-   -   % matching/stitching    -   % compute the difference of the data on the same physical        transmitter    -   % shared between block 1 and block 2    -   dd1=trans(6,:)-trans(9,:); (% index (6, 9) correspond to time of        measurement)    -   dd2=trans(7,:)-trans(10,:);    -   dd3=trans(5,:)-trans(8,:);    -   dd=(dd1+dd2+dd3)/3; % get an average    -   % shift the entire block 1    -   trans(1:7,:)=trans(1:7,:)-repmat(dd,7,1);    -   % compute the difference of the data on the same physical        transmitter    -   % shared between block 2 and block 3    -   dd1=trans(13,:)-trans(16,:);    -   dd2=trans(12,:)-trans(15,:);    -   dd3=trans(14,:)-trans(17,:);    -   dd=(dd1+dd2+dd3)/3;    -   % shift the entire block 3    -   trans(15:21,:)=trans(15:21,:)+repmat(dd,7,1);    -   % recombining the 21×27 into a final 15×27 removing redundant        data    -   trans=[trans(1:7,:); trans(11,:); trans(end-6:end,:)];    -   % this recombination may be done in different ways,    -   % to end up with a column of data per receiver.

FIG. 9 shows an example of the deconvolved image data (of FIG. 8) fortwo fingers touching the input device screen with the zero row sum CDM7drive matrix 610 in the presence of display noise after undergoing astitching and recombination process, according to an embodiment. As canbe seen, after stitching, in FIG. 9, an entire “touched” column/receivermoves with a single common mode zero-row-sum CDM artifact or noise, andthe CDM blocks are no longer independent. For the particular “stitching”used in this example, the shift in the column is the average of the dataon a column of CDM block 2. It should be noted that the finger on theleft is touching the second CDM block, but the finger on the right isnot, so there is no shift on the right side.

Image processing algorithms, e.g., to remove common-mode artifacts/noiseand clean up the entire image, may be performed. FIG. 10 shows anexample of the deconvolved image data (of FIG. 9) for two fingerstouching the input device screen with a zero row sum CDM7 in thepresence of display noise after undergoing a stitching and recombinationprocess and after removing common mode noise and artifacts, according toan embodiment. In FIG. 10, the fingers, the LGM artifacts, etc., areclearly distinct. IFP processing algorithms may be performed (e.g., tocorrect LGM if necessary, classify objects, etc.) as desired, so thatIFP may classify and report the two peaks as two fingers in thisexample.

A mathematical analysis of stitching, according to an embodiment, isprovided below.

As an example, consider 2 zero-row-sum CDM blocks A and B of order N.The measured data per transmitter, after deconvolution, is:

${\overset{arrow}{A}}^{(i)} = {{\overset{arrow}{s}}^{(i)} - {\frac{1}{N}{\sum\limits_{i = 1}^{N}{s^{arrow}}^{(j)}}} + {\alpha \; {\overset{arrow}{W}}^{:}}}$${\overset{arrow}{B}}^{(i)} = {{\overset{arrow}{t}}^{(i)} - {\frac{1}{N}{\sum\limits_{j = 1}^{N}{t^{arrow}}^{(j)}}} + {\beta \; {\overset{arrow}{W}}^{:}}}$

where, “i” is the transmitter index within the CDM block, s and trepresent the physical “finger” capacitance, W the display noise weightsand α and β random variables. The averages are averages within the CDMblock. Notice that for brevity any linear combination of weights isautomatically replaced with a single weight vector multiplied by a newrandom variable, which is the linear combination of the previous randomvariables, i.e.:

α{right arrow over (W)}+β{right arrow over (W)}=(α+β){right arrow over(W)}=γ{right arrow over (W)}

It should be noted that the distribution of γ is different from thedistribution of α and β, but the weights are the same, i.e. the vectorspace describing the display noise is not exited. Now, a name is givento the averages for compactness:

$\overset{\_}{\overset{arrow}{B}} = {\frac{1}{N}{\sum\limits_{i = 1}^{N}{\overset{arrow}{t}}^{(j)}}}$$\overset{\_}{\overset{arrow}{A}} = {\frac{1}{N}{\sum\limits_{i = 1}^{N}{\overset{arrow}{s}}^{(j)}}}$

The reported data after CDM deconvolution may be represented as:

{right arrow over (B)} ^((i)) ={right arrow over (t)} ^((i))−{rightarrow over ( B )}+β{right arrow over (W)}:

{right arrow over (A)} ^((i)) ={right arrow over (s)} ^((i))−{rightarrow over (Ā)}+β{right arrow over (W)}:

If there is a transmitter shared between the 2 CDM blocks and thedifference of the reported data for that same transmitter present in the2 different CDM blocks is computed, the “finger” signal cancels out toget a Delta equal to:

{right arrow over (Δ)}={right arrow over (B)} ^((i)) −{right arrow over(A)} ^((j)) ={right arrow over (t)} ^((i)) −{right arrow over (s)}^((j))−({right arrow over ( B )}−{right arrow over (Ā)})+γ{right arrowover (W)}=({right arrow over (Ā)}−{right arrow over ( B )})+γ{rightarrow over (W)}

The noise does not cancel out because there are 2 different noiserealizations in the 2 blocks, but the difference of the 2 noiserealizations is still in the same vector space, i.e. still proportionalto W, so Delta can be added to any other transmitter and a noisereduction algorithm would perform just the same.

Adding Delta to all the rows of the second CDM block B (to shift theentire block) results in:

{right arrow over (B)} ^((k)) +{right arrow over (Δ)}={right arrow over(t)} ^((k))−{right arrow over (Ā)}+δ{right arrow over (W)}

By inspection, comparing with block A, after noise removal there will beonly one common vector A to be determined for both blocks, i.e. onevalue per receiver for the entire frame (and no longer per CDM block),which is an easier problem to solve and also allows the use of morepowerful algorithms.

Following is an example of Matlab® code for stitching, according to anembodiment:

-   -   clear all;    -   % assuming CDM5 with 2 CDM blocks overlapping in 1 row    -   CDM=[0 −1 1 −1 1; −1 0 1 1 −1; 1 1 0 −1 −1; −1 1 −1 0 1; 1 −1 −1        1 0];    -   order=5;    -   assert(all(all(CDM*CDM′+ones(order)order*eye(order))))    -   w=1+(1:10)/10; % noise weights    -   sigma=10;    -   rng(1)    -   % physical background capacitance    -   base1=10*rand(5,10);    -   base2=10*rand(5,10);    -   base2(1,:)=base1(5,:); % same signal    -   r=sigma*(randn(5,1));    -   tempt=base1+r*w; % display noise realization    -   r=sigma*(randn(5,1));    -   temp2=base2+r*w; % display noise realization    -   a=(CDM′/order)*CDM*temp1+2048; % zero row sum removes the mean    -   b=(CDM′/order)*CDM*temp2+2048; % zero row sum removes the mean    -   % force matching: last transmitter of CDM block A and first        transmitter of CDM block B (which is the same transmitter)    -   db=a(5,:)-b(1,:); % difference    -   dB=1*repmat(db,5,1);    -   bp=b+dB; % apply the difference to entire block B    -   base=[a; bp(2:end,:)]; % recombine, and generate the first frame        to be passed to IFP    -   r=sigma*(randn(5,1));    -   temp1=base1+r*w; % new display noise realization    -   r=sigma*(randn(5,1));    -   temp2=base2+r*w; % new display noise realization    -   injectedDelta=10*(rand(7,7)-0.5);    -   temp1(2:5,3:9)=temp1(2:5,3:9)+injectedDelta(1:4,:);    -   a=(CDM′/order)*CDM*temp1+2048; % zero row sum removes the mean    -   temp2(1:4,3:9)=temp2(1:4,3:9)+injectedDelta(4:7,:);    -   b=(CDM′/order)*CDM*temp2+2048; % zero row sum removes the mean    -   % force matching: last transmitter of CDM block A and first        transmitter of CDM block B (which is the same transmitter)    -   db=a(5,:)-b(1,:); % difference    -   dB=1*repmat(db,5,1);    -   bp=b+dB; % apply the difference to entire block B    -   raw=[a; bp(2:end,:)]; % recombine, and generate the second frame        to be passed to IFP    -   %%% HERE STARTS IFP (IT RECEIVES REGULAR FRAMES)    -   delta=raw-base; % compute delta image    -   W=repmat(w,9,1); % remove disply noise, assumes first (left)        transmitter is untouched    -   deltaNew=delta./W;    -   col=repmat(deltaNew(:,1),1,10);    -   deltaNew=(deltaNew-col).*W    -   row=repmat(deltaNew(1,:),9,1); % fix minima, assumes first (top)        receiver is untouched    -   deltaNew=(deltaNew-row)    -   verify correction    -   error=deltaNew(2:8,3:9)-injectedDelta    -   assert(all(all(error<1e-8)))

In certain embodiments, it may be desirable to operate an input deviceto sense with a reduced set of sensing elements receivers, e.g., toreduce cost. For example, it may be desirable to sense with a firstsubset of a full set of receivers at one sensing iteration, and thensense with the remaining subset of receivers at one or more subsequentsensing iterations. In such a multiplexed sensing scheme, data acquiredby the disjoint sensing blocks (e.g., receiver subsets) may be used toform a single image. As an example, for a 12 receiver electrode inputdevice, transmitter electrodes may be activated and in a first sensingiteration, receiver electrodes 1-6 may be activated and in a secondsensing iteration, receiver electrodes 7-12 may be activated. The imagesfrom the two sensing iterations may be combined to form a full image.However, such multiplexed sensing may have drawbacks in the presence ofnoise. For example, if common mode noise is introduced in the data (bythe display, for example) it will have different realizations indifferent sensing iterations (muxes), making the noise difficult toremove since more free parameters need to be determined and fewerelectrodes are present in each of the sensing iteration (muxes) todistinguish signal from noise. Different sensing blocks are normallydisjoint, and since there may be a different noise realization in thecollected data for each block, the data from each sensing iteration(mux) needs to be cleaned separately, which can be challenging due tothe reduced number of electrodes in each block, which reduces theability to distinguish noise from signal (e.g., finger touch).

According to certain embodiments, as will be described in more detailbelow, one or more overlapping electrodes are used during each of thesensing iterations (muxes) to transform the “muxed” data into“non-muxed” data also in the presence of common mode noise. Overlappingthe receiver blocks so that they share one or more sensing elements orreceiver electrodes, and performing a stitching procedure,advantageously takes care of the differential noise problem at minimalcost. This advantageously removes the problem at the root and allows theuse of algorithms developed for non-multiplexed sensors. The embodimentsherein are useful for various sensing schemes, including 1-dimensionalabsolute sensing and 2-dimensional transcapacitive sensing schemes.

In an embodiment, a method of operating an input device having aplurality of receivers and a plurality of transmitters in a multiplexedmanner may include receiving, at a sensing region of the input device,an input, and driving the plurality of transmitters. Driving thetransmitters may include one of applying a voltage potential or acurrent to the transmitters. As the transmitters are driven, the methodfurther includes obtaining measurement signals over two or more receiverfiring steps or sensing iterations, wherein for each firing step orsensing iteration a subset of the full set of receivers are used oractivated and wherein each subset of receivers includes at least onereceiver in common with a prior subset. For example, in a first firingstep, first measurement signals corresponding to the input may beobtained using a first subset of the plurality of receivers of the inputdevice, and thereafter during a second firing step, second measurementsignals corresponding to the input may be obtained using a second subsetof the plurality of receivers of the input device, wherein the secondsubset includes at least one receiver in common with the first subset. Adifference between the first measurement signals and the secondmeasurement signals corresponding to the at least one receiver in commonmay be determined, and one of the first measurement signals or thesecond measurement signals may be adjusted based on the determineddifference to produce noise-corrected measurement signals. In certainaspects, during each firing step, the plurality of receivers used oractivated for that step are used or activated simultaneously.

FIG. 11 shows an example of data acquired in two receiver firing stepsor sensing iterations with one overlapping receiver electrode for a setof 11 receiver electrodes, according to an embodiment. In a firstsensing iteration, receiver electrodes 1-6 are activated to obtain afirst set of measurement signals (“left mux” in FIG. 11), and in asecond sensing iteration receiver electrodes 6-11 are activated toobtain a second set of measurement signals (“right mux” in FIG. 11),with receiver electrode 6 in common between the sensing iterations. Ascan be seen in this example, in the presence of noise, a difference intiming between the first sensing iteration and the second sensingiteration may result in a noise difference component (e.g., noise maychange over time) detected in the measurements, as is evidenced by thedifference in values for the common receiver, e.g., electrode 6. In anembodiment, the difference of the value for the common receiver betweeniterations may be used to determine an amount to shift the first set ofmeasurement signals, or the second set of measurement signals, to removethe noise difference component between sensing iterations.

In an embodiment, a process for determining the noise differencecomponent and correcting a set of measurements for two measurementiteration may be done according to the following:

d _(i) ⁽¹⁾ =s _(i) ⁽¹⁾ +αW _(i) for i=1 to N ⁽¹⁾

d _(i) ⁽²⁾ =s _(i) ⁽²⁾ +βW _(i) for i=N ⁽²⁾ to N

where d is the measured data, s the “finger” signal, α and β arenormally distributed random variables representing a noiseinstantiation, W are the noise weights that represent the common modenoise amplitude per receiver, i is the electrode number, N⁽¹⁾ is thenumber of electrodes in measurement iteration (mux) 1, N−N⁽²⁾ is thenumber of electrodes in mux 2, and N is the total number of electrodes.

Normally N⁽²⁾=N⁽¹⁾+1, but here N⁽²⁾≤N⁽¹⁾ instead. Also, assuming thatthere is one electrode in common, i.e. N⁽²⁾=N⁽¹⁾=k, one can then define:

$\Delta_{k} = {\frac{d_{k}^{(1)} - d_{k}^{(2)}}{W_{k}} = {\frac{s_{k}^{(1)} - s_{k}^{(2)} + {( {\alpha - \beta} )W_{k}}}{W_{k}} = ( {a - \beta} )}}$

assuming the finger signal cancels out. Now A_(k) is added to all pixelsof the second mux to get:

d _(i) ⁽²⁾ =s _(i) ⁽²⁾ +βW _(i)+Δ_(k) W _(i) =s _(i) ⁽²⁾ +αW _(i) fori=N ⁽²⁾ to N

which reduces the problem to the original non-muxing common mode noiseremoval problem because d_(i)=s_(i)+αW_(i) for i=1 to N, i.e. there isonly 1 parameter, α, to be determined.

FIG. 11 also shows results of a stitching or shifting procedure tocorrect for a noise difference between the sensing steps, according toan embodiment. As shown, the data for electrodes i=N⁽²⁾ to N=electrodes6 to 11 are shifted to correct for the noise difference (“shifted rightmux” in FIG. 11).

If there is more than one electrode in common and only 1 noisecomponent, one can compute multiple Δs and take an average. Also, if thenoise has multiple components, and the components are not linearlydependent on the shared electrodes, a “multiple-component” stitching maybe performed.

FIG. 12 shows an example of data acquired in two receiver firing stepsor sensing iterations with two overlapping receiver electrodes for a setof 11 receiver electrodes, according to an embodiment. In a firstsensing iteration, receiver electrodes 1-6 are activated to obtain afirst set of measurement signals (“left mux” in FIG. 12), and in asecond sensing iteration receiver electrodes 5-11 are activated toobtain a second set of measurement signals (“right mux” in FIG. 12),with receiver electrodes 5 and 6 in common between sensing iterations.As can be seen in this example, in the presence of noise, the differencein timing between the first sensing iteration and the second sensingiteration may result in a noise difference component (e.g., noise maychange over time), as is evidenced by the difference in values for thecommon receivers, e.g., receiver electrodes 5 and 6. In an embodiment,the difference in value for the common receivers may be used todetermine an amount to shift the first set of measurement signals, orthe second set of measurement signals, to remove the noise differencebetween sensing iterations. FIG. 12 also shows results of a stitching orshifting procedure to correct for a noise difference between the sensingiterations with two receiver electrodes in common, according to anembodiment. As shown, the data for receiver electrodes 5 to 11 areshifted to correct for the noise difference (“shifted right mux” in FIG.12).

FIG. 13 is a flowchart depicting an example process for sensing an inputwith an input device using CDM, according to an embodiment. At stage1001, an input, such as a biometric object or objects (e.g., one or morefingers) or a stylus, is received at a sensing region of the inputdevice. At stage 1002, imaging is performed by the input device usingCDM, for example, using a CDM drive matrix including constituent CDMblocks overlapping at one or more transmitters as described herein. Theperformed imaging may include, for example, a processing systemdeconvolving or decoding raw information obtained using the CDMtechniques. At stage 1003, the detected image may be optionallyprocessed further, if appropriate, for example using IFP techniques. Atstage 1004, various functions (such as touch sensing, navigationfunctions, authentication, etc.) may be performed by the processingsystem based on the detected and/or processed image.

The various embodiments herein are useful for square wave sensing, sinewave sensing or any sensing modulation/shaping pattern.

It will be appreciated that although the illustrative examples discussedabove are provided in the context of capacitive input devices, theprinciples described herein may also be applied to other types of inputdevices, such as acoustic or ultrasonic input devices, which alsoutilize transmitters and receivers. For example, the transmitters of anacoustic or ultrasonic input device may also be driven over multipleiterations using a lower-order overlapping CDM techniques as describedherein.

U.S. patent application Ser. No. 15/720,817, filed Sep. 29, 2017, andU.S. patent application Ser. No. 16/132,773, filed Sep. 17, 2018, whichare incorporated herein by reference, discloses various aspects of inputsensing using CDM drive matrices.

All references, including publications, patent applications, andpatents, cited herein are hereby incorporated by reference to the sameextent as if each reference were individually and specifically indicatedto be incorporated by reference and were set forth in its entiretyherein.

The use of the terms “a” and “an” and “the” and “at least one” andsimilar referents in the context of describing the invention (especiallyin the context of the following claims) are to be construed to coverboth the singular and the plural, unless otherwise indicated herein orclearly contradicted by context. The use of the term “at least one”followed by a list of one or more items (for example, “at least one of Aand B”) is to be construed to mean one item selected from the listeditems (A or B) or any combination of two or more of the listed items (Aand B), unless otherwise indicated herein or clearly contradicted bycontext. The terms “comprising,” “having,” “including,” and “containing”are to be construed as open-ended terms (i.e., meaning “including, butnot limited to,”) unless otherwise noted. Recitation of ranges of valuesherein are merely intended to serve as a shorthand method of referringindividually to each separate value falling within the range, unlessotherwise indicated herein, and each separate value is incorporated intothe specification as if it were individually recited herein. All methodsdescribed herein can be performed in any suitable order unless otherwiseindicated herein or otherwise clearly contradicted by context. The useof any and all examples, or exemplary language (e.g., “such as”)provided herein, is intended merely to better illuminate the inventionand does not pose a limitation on the scope of the invention unlessotherwise claimed. No language in the specification should be construedas indicating any non-claimed element as essential to the practice ofthe invention.

Exemplary embodiments are described herein. Variations of thoseexemplary embodiments may become apparent to those of ordinary skill inthe art upon reading the foregoing description. The inventors expectskilled artisans to employ such variations as appropriate, and theinventors intend for the invention to be practiced otherwise than asspecifically described herein. Accordingly, this invention includes allmodifications and equivalents of the subject matter recited in theclaims appended hereto as permitted by applicable law. Moreover, anycombination of the above-described elements in all possible variationsthereof is encompassed by the invention unless otherwise indicatedherein or otherwise clearly contradicted by context.

1. A method of input sensing using an input device, the methodcomprising: receiving, at a sensing region of the input device, one ormore inputs; and obtaining, using a plurality of receivers of the inputdevice, measurement signals corresponding to the one or more inputs,wherein obtaining the measurement signals comprises: driving a firstsubset of transmitters of the input device according to a first portionof a CDM drive matrix, wherein the CDM matrix is a zero row sum matrix,and obtaining first measurement signals with the plurality of receivers;and driving a second subset of the transmitters according to a secondportion of the CDM drive matrix, wherein the first and second subsets oftransmitters include at least one transmitter in common, and obtainingsecond measurement signals with the plurality of receivers.
 2. Themethod of claim 1, wherein each of the first and second subsets oftransmitters comprises a plurality of non-contiguous transmitters. 3.The method of claim 2, wherein at least one of the first and secondsubsets of transmitters includes at least two contiguous transmitters.4. The method of claim 1, wherein the zero row sum CDM drive matrix hasan odd dimension or the zero row sum CDM drive matrix has an evendimension or the zero row sum CDM drive matrix includes a circulantmatrix.
 5. The method of claim 1, wherein the plurality of receiverscomprises a subset of all the receivers of the input device.
 6. Themethod according to claim 1, further comprising generating, by aprocessing system, an image of the one or more inputs based on theobtained first and second measurement signals, wherein the generatingthe image includes decoding the obtained first and second measurementsignals using the inverse or transpose of the corresponding first orsecond portion of the CDM drive matrix for the first and second drivensubsets of transmitters to obtain image information.
 7. The method ofclaim 1, wherein the input device includes a transcapacitive inputdevice and wherein the transmitters are transmitter electrodes, and thereceivers are receiver electrodes.
 8. The method of claim 1, wherein thefirst and second subsets of transmitters include more than onetransmitter in common.
 9. The method of claim 1, wherein the obtainingmeasurement signals further includes driving a third subset of thetransmitters according to the CDM drive matrix, wherein the third subsetof transmitters includes at least one transmitter in common with thefirst subset of transmitters or the second subset of transmitters, andobtaining third measurement signals with the plurality of receivers. 10.An input device for sensing a biometric object, the input devicecomprising: a surface corresponding to a sensing region, wherein thesensing region is configured to receive one or more inputs;transmitters, configured to be driven with transmitter signals; andreceivers, configured to obtain measurement signals corresponding to theone or more inputs, by: driving a first subset of the transmittersaccording to a first portion of a CDM drive matrix, wherein the CDMmatrix is a zero row sum matrix, and obtaining first measurement signalswith the receivers, and thereafter driving a second subset of thetransmitters according to a second portion of the CDM drive matrix,wherein the first and second subsets of transmitters include at leastone transmitter in common, and obtaining second measurement signals withthe receivers.
 11. The input device of claim 10, wherein each of thefirst and second subsets of the transmitters comprises a plurality ofnon-contiguous transmitters.
 12. The input device of claim 11, whereinat least one of the first and second subsets of the transmittersincludes at least two contiguous transmitters
 13. The input device ofclaim 10, further comprising a processing system configured to generatean image of the one or more inputs based on the obtained first andsecond measurement signals by decoding the obtained first and secondmeasurement signals using the inverse or transpose of the correspondingfirst or second portion of the CDM drive matrix for the first and seconddriven subsets of transmitters to obtain image information.
 14. Theinput device of claim 10, wherein the input device is a transcapacitiveinput device, the transmitters are transmitter electrodes, and thereceivers are receiver electrodes.
 15. The input device of claim 10,wherein the zero row sum CDM drive matrix has an odd dimension or thezero row sum CDM drive matrix has an even dimension or the zero row sumCDM drive matrix includes a circulant matrix.
 16. The input device ofclaim 10, wherein the first and second subsets of the transmittersinclude more than one transmitter in common.
 17. A non-transitorycomputer-readable medium having processor-executable instructions storedthereon for performing input sensing using an input device, theprocessor-executable instructions, when executed by a processing system,enable the processing system to implement the following method:obtaining, via receivers of the input device, measurement signalscorresponding to one or more inputs received at a sensing region of theinput device, wherein obtaining the measurement signals comprises:driving a first subset of transmitters of the input device according toa first portion of a CDM drive matrix, wherein the CDM matrix is a zerorow sum matrix, and obtaining first measurement signals with thereceivers, and driving a second subset of the transmitters according toa second portion of the CDM drive matrix, wherein the first and secondsubsets of transmitters include at least one transmitter in common, andobtaining second measurement signals with the receivers; and generatingan image of the one or more inputs by processing the first measurementsignals and the second measurement signals.
 18. The non-transitorycomputer-readable medium of claim 17, wherein the generating the imageincludes decoding the obtained first and second measurement signalsusing the inverse or transpose of the corresponding first or secondportion of the CDM drive matrix for the first and second driven subsetsof transmitters to obtain image information.
 19. The non-transitorycomputer-readable medium of claim 17, wherein the input device is atranscapacitive input device, the transmitters are transmitterelectrodes, and the receivers are receiver electrodes.